Chapter 12 Source of functional differences
# A tibble: 4 × 2
type_river count
<chr> <int>
1 absent 3
2 core 389
3 endemic 99
4 marginal 48***************************************************************
* Note: *
* force.ultrametric does not include a formal method to *
* ultrametricize a tree & should only be used to coerce *
* a phylogeny that fails is.ultrametric due to rounding -- *
* not as a substitute for formal rate-smoothing methods. *
***************************************************************12.1 Taxonomic variation
genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
left_join(., sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
filter(count > 0) %>% #filter 0 counts
left_join(core_microbiota,by="genome") %>%
group_by(type,sample) %>%
summarise(fraction=sum(count)) %>%
group_by(type) %>%
summarise(mean(fraction))`summarise()` has grouped output by 'type'. You can override using the `.groups` argument.# A tibble: 4 × 2
type `mean(fraction)`
<chr> <dbl>
1 core 0.870
2 endemic 0.0882
3 marginal 0.0407
4 <NA> 0.074612.2 MAGs in different locations and shared among locations
12.2.1 Core
genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
left_join(., sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
filter(count > 0) %>% #filter 0 counts
left_join(core_microbiota,by="genome") %>%
filter(type=="core") %>%
ggplot(., aes(x=sample,y=count, fill=phylum, group=phylum)) + #grouping enables keeping the same sorting of taxonomic units
geom_bar(stat="identity", colour="white", linewidth=0.1) + #plot stacked bars with white borders
scale_fill_manual(values=phylum_colors) +
facet_nested(~factor(environment, labels=c("low" = "Low altitude", "high" = "High altitude")), scales="free") + #facet per day and treatment
guides(fill = guide_legend(ncol = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
strip.background = element_rect(fill = "white"),
strip.text = element_text(size = 12, lineheight = 0.6,face="bold"),
axis.line = element_line(linewidth = 0.5, linetype = "solid", colour = "black")) +
labs(fill="Phylum",y = "Relative abundance",x="Samples")
12.2.2 Endemic
genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
left_join(., sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
filter(count > 0) %>% #filter 0 counts
left_join(core_microbiota,by="genome") %>%
filter(type=="endemic") %>%
ggplot(., aes(x=sample,y=count, fill=phylum, group=phylum)) + #grouping enables keeping the same sorting of taxonomic units
geom_bar(stat="identity", colour="white", linewidth=0.1) + #plot stacked bars with white borders
scale_fill_manual(values=phylum_colors) +
ylim(0,1)+
facet_nested(~factor(environment, labels=c("low" = "Low altitude", "high" = "High altitude")), scales="free") + #facet per day and treatment
guides(fill = guide_legend(ncol = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
strip.background = element_rect(fill = "white"),
strip.text = element_text(size = 12, lineheight = 0.6,face="bold"),
axis.line = element_line(linewidth = 0.5, linetype = "solid", colour = "black")) +
labs(fill="Phylum",y = "Relative abundance",x="Samples")
12.2.3 Marginal
genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
left_join(., sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
filter(count > 0) %>% #filter 0 counts
left_join(core_microbiota,by="genome") %>%
filter(type=="marginal") %>%
ggplot(., aes(x=sample,y=count, fill=phylum, group=phylum)) + #grouping enables keeping the same sorting of taxonomic units
geom_bar(stat="identity", colour="white", linewidth=0.1) + #plot stacked bars with white borders
ylim(0,1)+
scale_fill_manual(values=phylum_colors) +
facet_nested(~factor(environment, labels=c("low" = "Low altitude", "high" = "High altitude")), scales="free") + #facet per day and treatment
guides(fill = guide_legend(ncol = 1)) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.x = element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
strip.background = element_rect(fill = "white"),
strip.text = element_text(size = 12, lineheight = 0.6,face="bold"),
axis.line = element_line(linewidth = 0.5, linetype = "solid", colour = "black")) +
labs(fill="Phylum",y = "Relative abundance",x="Samples")
12.2.4 Ordination
gift_pcoa <- genome_gifts[, !grepl("^S", colnames(genome_gifts))] %>%
to.elements(., GIFT_db) %>%
as.data.frame() %>%
vegdist(method="euclidean") %>%
pcoa()
gift_pcoa_rel_eigen <- gift_pcoa$values$Relative_eig[1:10]
# Get genome positions
gift_pcoa_vectors <- gift_pcoa$vectors %>% #extract vectors
as.data.frame() %>%
select(Axis.1,Axis.2) # keep the first 2 axes
gift_pcoa_eigenvalues <- gift_pcoa$values$Eigenvalues[c(1,2)]
gift_pcoa_gifts <- cov(genome_gifts, scale(gift_pcoa_vectors)) %*% diag((gift_pcoa_eigenvalues/(nrow(genome_gifts)-1))^(-0.5)) %>%
as.data.frame() %>%
rename(Axis.1=1,Axis.2=2) %>%
rownames_to_column(var="label") %>%
#get function summary vectors
mutate(func=substr(label,1,3)) %>%
group_by(func) %>%
summarise(Axis.1=mean(Axis.1),
Axis.2=mean(Axis.2)) %>%
rename(label=func) %>%
filter(!label %in% c("S01","S02","S03"))set.seed(101)
scale <- 20 # scale for vector loadings
gift_pcoa_vectors %>%
rownames_to_column(var="genome") %>%
left_join(genome_metadata, by="genome") %>%
ggplot() +
#genome positions
scale_color_manual(values=phylum_colors)+
geom_point(aes(x=Axis.1,y=Axis.2, color=phylum, size=length),
alpha=0.9, shape=16) +
#scale_color_manual(values=phylum_colors) +
scale_size_continuous(range = c(0.1,5)) +
#loading positions
geom_segment(data=gift_pcoa_gifts,
aes(x=0, y=0, xend=Axis.1 * scale, yend=Axis.2 * scale),
arrow = arrow(length = unit(0.3, "cm"),
type = "open",
angle = 25),
linewidth = 0.5,
color = "black") +
#Primary and secondary scale adjustments
scale_x_continuous(name = paste0("PCoA1 (",round(gift_pcoa_rel_eigen[1]*100, digits = 2), " %)"),
sec.axis = sec_axis(~ . / scale, name = "Loadings on PCoA1")
) +
scale_y_continuous(name = paste0("PCoA2 (",round(gift_pcoa_rel_eigen[2]*100, digits = 2), " %)"),
sec.axis = sec_axis(~ . / scale, name = "Loadings on PCoA2")
) +
geom_label_repel(data = gift_pcoa_gifts,
aes(label = label, x = Axis.1 * scale, y = Axis.2 * scale),
segment.color = 'transparent') +
xlim(-4.5,4.5) +
ylim(-3,2.5) +
theme_minimal() +
theme(legend.position = "none")
structural <- core_microbiota %>%
mutate(type = case_when(
(type_prevalence == "endemic") & (type_prevalence_environment == "high") ~ "present_high",
(type_prevalence == "endemic") & (type_prevalence_environment == "low") ~ "present_low")) %>%
filter(!is.na(type)) %>%
select(genome,type)
enriched <- ancom_mag_gut_table %>%
mutate(type = case_when(
lfc_environmentlow < 0 ~ "enriched_low",
lfc_environmentlow >= 0 ~ "enriched_high")) %>%
select(genome,type)
scale <- 15 # scale for vector loadings
gift_pcoa_vectors %>%
rownames_to_column(var="genome") %>%
left_join(bind_rows(structural,enriched), by="genome") %>%
left_join(genome_metadata, by="genome") %>%
mutate(type=ifelse(is.na(type),"neutral",type)) %>%
group_by(type) %>%
mutate(x_cen = median(Axis.1, na.rm = TRUE)) %>%
mutate(y_cen = median(Axis.2, na.rm = TRUE)) %>%
ungroup() %>%
ggplot() +
scale_size_continuous(range = c(0.1,5)) +
geom_point(aes(x=Axis.1,y=Axis.2, color=type, size=length), alpha=0.9, shape=16) +
geom_segment(aes(x = x_cen, y = y_cen, xend = Axis.1, yend = Axis.2, color=type), alpha = 0.5) +
scale_color_manual(values=c("#5A99D2","#F16144","#B7B7B7","#225072","#8C2C1C"))+
theme_minimal() +
theme(legend.position = "none")
scale <- 15 # scale for vector loadings
gift_pcoa_vectors %>%
rownames_to_column(var="genome") %>%
left_join(core_microbiota, by="genome") %>%
left_join(genome_metadata, by="genome") %>%
filter(type != "absent") %>%
mutate(shape = case_when(
type == "core" ~ "core",
type == "marginal" ~ "marginal",
type == "endemic" & type_prevalence_environment == "high" ~ "endemic_high",
type == "endemic" & type_prevalence_environment == "low" ~ "endemic_low"
)) %>%
group_by(shape) %>%
mutate(x_cen = median(Axis.1, na.rm = TRUE)) %>%
mutate(y_cen = median(Axis.2, na.rm = TRUE)) %>%
ungroup() %>%
ggplot() +
#genome positions
geom_segment(aes(x = x_cen, y = y_cen, xend = Axis.1, yend = Axis.2, color=shape), alpha = 0.5, show.legend = FALSE) +
scale_color_manual(values=c("#9E8F71","#5A99D2","#F16144","#B7B7B7"))+
theme_minimal() 
12.3 Functional variation
12.3.1 Core
# A tibble: 0 × 5
# ℹ 5 variables: gift <chr>, high <dbl>, low <dbl>, p_value <dbl>, p_adjust <dbl>
Wilcoxon rank sum exact test
data: mci by environment
W = 55, p-value = 0.01643
alternative hypothesis: true location shift is not equal to 0# A tibble: 0 × 7
# ℹ 7 variables: gift <chr>, high <dbl>, low <dbl>, p_value <dbl>, p_adjust <dbl>, difference <dbl>, significance <chr>
| term | df | SumOfSqs | R2 | statistic | p.value |
|---|---|---|---|---|---|
| environment | 1 | 0.7158447 | 0.06965384 | 2.136654 | 0.051 |
| river | 2 | 0.8505330 | 0.08275942 | 1.269336 | 0.223 |
| Residual | 26 | 8.7107971 | 0.84758674 | NA | NA |
| Total | 29 | 10.2771749 | 1.00000000 | NA | NA |
12.3.2 Endemic
Wilcoxon rank sum exact test
data: mci by environment
W = 24, p-value = 8.979e-05
alternative hypothesis: true location shift is not equal to 0| gift | high | low | p_value | p_adjust |
|---|---|---|---|---|
| B0104 | 0.318371850 | 0.477248051 | 4.266185e-03 | 8.738798e-03 |
| B0106 | 0.652417204 | 0.750373702 | 2.349615e-02 | 3.825655e-02 |
| B0204 | 0.272751511 | 0.411834564 | 9.967024e-04 | 2.751765e-03 |
| B0205 | 0.349827863 | 0.607824698 | 2.150627e-04 | 7.803705e-04 |
| B0207 | 0.349413509 | 0.607091324 | 8.978999e-05 | 4.072617e-04 |
| B0208 | 0.277418167 | 0.571441654 | 1.125340e-04 | 4.610265e-04 |
| B0209 | 0.418950756 | 0.654470027 | 1.665215e-03 | 3.916339e-03 |
| B0210 | 0.314626667 | 0.599130873 | 2.701874e-03 | 5.815898e-03 |
| B0211 | 0.505796266 | 0.763739750 | 2.514223e-06 | 6.450676e-05 |
| B0212 | 0.341025004 | 0.546199073 | 4.939623e-03 | 9.802064e-03 |
| B0213 | 0.415890582 | 0.550634314 | 1.643172e-02 | 2.782438e-02 |
| B0215 | 0.255319614 | 0.554385824 | 5.777813e-04 | 1.834456e-03 |
| B0216 | 0.105448827 | 0.426833768 | 2.041033e-05 | 1.993932e-04 |
| B0217 | 0.281630700 | 0.400857555 | 6.955501e-04 | 2.154509e-03 |
| B0220 | 0.108696049 | 0.075493630 | 9.874823e-03 | 1.717949e-02 |
| B0221 | 0.255637379 | 0.383346961 | 9.874823e-03 | 1.717949e-02 |
| B0303 | 0.168217937 | 0.258794974 | 2.643028e-04 | 8.833279e-04 |
| B0309 | 0.028042752 | 0.096603777 | 7.399332e-03 | 1.408868e-02 |
| B0310 | 0.000000000 | 0.039314500 | 8.257612e-03 | 1.519879e-02 |
| B0402 | 0.556281087 | 0.493520756 | 1.408119e-03 | 3.804919e-03 |
| B0601 | 0.382208213 | 0.577022449 | 2.654761e-05 | 2.408248e-04 |
| B0602 | 0.506114317 | 0.745114749 | 1.403581e-04 | 5.401660e-04 |
| B0603 | 0.260255972 | 0.467609340 | 5.618966e-05 | 3.161839e-04 |
| B0701 | 0.432395583 | 0.679531792 | 8.978999e-05 | 4.072617e-04 |
| B0703 | 0.022340365 | 0.156111414 | 5.726164e-05 | 3.161839e-04 |
| B0704 | 0.312937738 | 0.598325101 | 3.432236e-05 | 2.564082e-04 |
| B0705 | 0.184992803 | 0.398754859 | 1.554950e-05 | 1.645656e-04 |
| B0706 | 0.336719078 | 0.509754909 | 7.543545e-03 | 1.408868e-02 |
| B0707 | 0.584533168 | 0.687871927 | 7.543545e-03 | 1.408868e-02 |
| B0710 | 0.016909779 | 0.108809582 | 1.581108e-03 | 3.916339e-03 |
| B0711 | 0.208154526 | 0.416638817 | 7.121052e-05 | 3.617495e-04 |
| B0712 | 0.099046619 | 0.204586247 | 5.703508e-03 | 1.114378e-02 |
| B0804 | 0.456763954 | 0.763616891 | 1.177172e-05 | 1.359099e-04 |
| B0805 | 0.042739966 | 0.173618219 | 5.802053e-07 | 4.360009e-05 |
| B0901 | 0.100157586 | 0.041913672 | 1.665215e-03 | 3.916339e-03 |
| B0903 | 0.000000000 | 0.019080084 | 2.539636e-06 | 6.450676e-05 |
| B1004 | 0.125149306 | 0.140982835 | 8.964396e-03 | 1.603490e-02 |
| B1012 | 0.001356128 | 0.019240248 | 1.619167e-04 | 6.048064e-04 |
| B1014 | 0.022601362 | 0.000000000 | 2.539636e-06 | 6.450676e-05 |
| D0104 | 0.058683884 | 0.159932473 | 2.306458e-03 | 5.050347e-03 |
| D0201 | 0.092234219 | 0.260028653 | 8.340902e-04 | 2.407488e-03 |
| D0202 | 0.160795013 | 0.371123533 | 5.618966e-05 | 3.161839e-04 |
| D0203 | 0.342605111 | 0.471551663 | 3.432236e-05 | 2.564082e-04 |
| D0204 | 0.250243216 | 0.395633777 | 2.306458e-03 | 5.050347e-03 |
| D0205 | 0.063752861 | 0.169920437 | 7.121052e-05 | 3.617495e-04 |
| D0206 | 0.147551315 | 0.443090128 | 5.618966e-05 | 3.161839e-04 |
| D0207 | 0.412156668 | 0.558207530 | 2.090231e-02 | 3.447523e-02 |
| D0208 | 0.155823369 | 0.301738922 | 5.618966e-05 | 3.161839e-04 |
| D0209 | 0.131997770 | 0.352678185 | 6.549873e-06 | 9.242598e-05 |
| D0210 | 0.133702102 | 0.284613983 | 1.177172e-05 | 1.359099e-04 |
| D0212 | 0.133552981 | 0.422562064 | 6.549873e-06 | 9.242598e-05 |
| D0213 | 0.126218478 | 0.306630447 | 8.340902e-04 | 2.407488e-03 |
| D0305 | 0.366492686 | 0.423996527 | 4.939623e-03 | 9.802064e-03 |
| D0306 | 0.146105878 | 0.434641186 | 6.549873e-06 | 9.242598e-05 |
| D0501 | 0.790847790 | 0.872992541 | 1.805380e-02 | 3.016885e-02 |
| D0502 | 0.480358478 | 0.285918054 | 4.781407e-04 | 1.557022e-03 |
| D0503 | 0.125879327 | 0.000000000 | 6.866156e-07 | 4.360009e-05 |
| D0505 | 0.286597240 | 0.350858031 | 8.641809e-03 | 1.567871e-02 |
| D0506 | 0.211360464 | 0.391670686 | 6.549873e-06 | 9.242598e-05 |
| D0507 | 0.110052668 | 0.210004157 | 1.125340e-04 | 4.610265e-04 |
| D0509 | 0.440041988 | 0.526487614 | 1.125601e-02 | 1.931774e-02 |
| D0510 | 0.000000000 | 0.013573683 | 2.308808e-04 | 7.924829e-04 |
| D0511 | 0.611751724 | 0.767405683 | 1.665215e-03 | 3.916339e-03 |
| D0513 | 0.224858211 | 0.438902945 | 3.155375e-03 | 6.678878e-03 |
| D0601 | 0.034174614 | 0.141369358 | 2.997491e-02 | 4.758517e-02 |
| D0602 | 0.000000000 | 0.030499587 | 2.308808e-04 | 7.924829e-04 |
| D0606 | 0.003034342 | 0.043637689 | 5.152105e-05 | 3.161839e-04 |
| D0607 | 0.008552574 | 0.041697052 | 2.096373e-03 | 4.840715e-03 |
| D0608 | 0.000000000 | 0.002444638 | 3.625355e-03 | 7.547870e-03 |
| D0609 | 0.158687978 | 0.084565489 | 1.403581e-04 | 5.401660e-04 |
| D0610 | 0.000000000 | 0.007160308 | 1.522953e-03 | 3.916339e-03 |
| D0702 | 0.455688142 | 0.326464654 | 2.635404e-02 | 4.236663e-02 |
| D0705 | 0.323241782 | 0.258159545 | 2.306458e-03 | 5.050347e-03 |
| D0706 | 0.059976159 | 0.148351231 | 1.665215e-03 | 3.916339e-03 |
| D0807 | 0.015074471 | 0.041747020 | 8.978999e-05 | 4.072617e-04 |
| D0816 | 0.043641253 | 0.091390659 | 8.340902e-04 | 2.407488e-03 |
| D0817 | 0.005827776 | 0.019925548 | 1.445050e-03 | 3.823361e-03 |
| D0907 | 0.162914556 | 0.328681837 | 9.967024e-04 | 2.751765e-03 |
| D0908 | 0.305403136 | 0.623522292 | 3.432236e-05 | 2.564082e-04 |
| D0910 | 0.124407773 | 0.396891803 | 1.125340e-04 | 4.610265e-04 |
| gift | high | low | p_value | p_adjust | difference | significance |
|---|---|---|---|---|---|---|
| B0104 | 0.318371850 | 0.477248051 | 4.266185e-03 | 8.738798e-03 | -0.158876201 | significant |
| B0106 | 0.652417204 | 0.750373702 | 2.349615e-02 | 3.825655e-02 | -0.097956497 | significant |
| B0204 | 0.272751511 | 0.411834564 | 9.967024e-04 | 2.751765e-03 | -0.139083053 | significant |
| B0205 | 0.349827863 | 0.607824698 | 2.150627e-04 | 7.803705e-04 | -0.257996835 | significant |
| B0207 | 0.349413509 | 0.607091324 | 8.978999e-05 | 4.072617e-04 | -0.257677815 | significant |
| B0208 | 0.277418167 | 0.571441654 | 1.125340e-04 | 4.610265e-04 | -0.294023487 | significant |
| B0209 | 0.418950756 | 0.654470027 | 1.665215e-03 | 3.916339e-03 | -0.235519272 | significant |
| B0210 | 0.314626667 | 0.599130873 | 2.701874e-03 | 5.815898e-03 | -0.284504206 | significant |
| B0211 | 0.505796266 | 0.763739750 | 2.514223e-06 | 6.450676e-05 | -0.257943484 | significant |
| B0212 | 0.341025004 | 0.546199073 | 4.939623e-03 | 9.802064e-03 | -0.205174069 | significant |
| B0213 | 0.415890582 | 0.550634314 | 1.643172e-02 | 2.782438e-02 | -0.134743732 | significant |
| B0215 | 0.255319614 | 0.554385824 | 5.777813e-04 | 1.834456e-03 | -0.299066210 | significant |
| B0216 | 0.105448827 | 0.426833768 | 2.041033e-05 | 1.993932e-04 | -0.321384940 | significant |
| B0217 | 0.281630700 | 0.400857555 | 6.955501e-04 | 2.154509e-03 | -0.119226854 | significant |
| B0220 | 0.108696049 | 0.075493630 | 9.874823e-03 | 1.717949e-02 | 0.033202420 | significant |
| B0221 | 0.255637379 | 0.383346961 | 9.874823e-03 | 1.717949e-02 | -0.127709582 | significant |
| B0303 | 0.168217937 | 0.258794974 | 2.643028e-04 | 8.833279e-04 | -0.090577037 | significant |
| B0309 | 0.028042752 | 0.096603777 | 7.399332e-03 | 1.408868e-02 | -0.068561026 | significant |
| B0310 | 0.000000000 | 0.039314500 | 8.257612e-03 | 1.519879e-02 | -0.039314500 | significant |
| B0402 | 0.556281087 | 0.493520756 | 1.408119e-03 | 3.804919e-03 | 0.062760331 | significant |
| B0601 | 0.382208213 | 0.577022449 | 2.654761e-05 | 2.408248e-04 | -0.194814235 | significant |
| B0602 | 0.506114317 | 0.745114749 | 1.403581e-04 | 5.401660e-04 | -0.239000432 | significant |
| B0603 | 0.260255972 | 0.467609340 | 5.618966e-05 | 3.161839e-04 | -0.207353368 | significant |
| B0701 | 0.432395583 | 0.679531792 | 8.978999e-05 | 4.072617e-04 | -0.247136209 | significant |
| B0703 | 0.022340365 | 0.156111414 | 5.726164e-05 | 3.161839e-04 | -0.133771050 | significant |
| B0704 | 0.312937738 | 0.598325101 | 3.432236e-05 | 2.564082e-04 | -0.285387364 | significant |
| B0705 | 0.184992803 | 0.398754859 | 1.554950e-05 | 1.645656e-04 | -0.213762056 | significant |
| B0706 | 0.336719078 | 0.509754909 | 7.543545e-03 | 1.408868e-02 | -0.173035831 | significant |
| B0707 | 0.584533168 | 0.687871927 | 7.543545e-03 | 1.408868e-02 | -0.103338760 | significant |
| B0710 | 0.016909779 | 0.108809582 | 1.581108e-03 | 3.916339e-03 | -0.091899802 | significant |
| B0711 | 0.208154526 | 0.416638817 | 7.121052e-05 | 3.617495e-04 | -0.208484291 | significant |
| B0712 | 0.099046619 | 0.204586247 | 5.703508e-03 | 1.114378e-02 | -0.105539628 | significant |
| B0804 | 0.456763954 | 0.763616891 | 1.177172e-05 | 1.359099e-04 | -0.306852936 | significant |
| B0805 | 0.042739966 | 0.173618219 | 5.802053e-07 | 4.360009e-05 | -0.130878253 | significant |
| B0901 | 0.100157586 | 0.041913672 | 1.665215e-03 | 3.916339e-03 | 0.058243913 | significant |
| B0903 | 0.000000000 | 0.019080084 | 2.539636e-06 | 6.450676e-05 | -0.019080084 | significant |
| B1004 | 0.125149306 | 0.140982835 | 8.964396e-03 | 1.603490e-02 | -0.015833529 | significant |
| B1012 | 0.001356128 | 0.019240248 | 1.619167e-04 | 6.048064e-04 | -0.017884120 | significant |
| B1014 | 0.022601362 | 0.000000000 | 2.539636e-06 | 6.450676e-05 | 0.022601362 | significant |
| D0104 | 0.058683884 | 0.159932473 | 2.306458e-03 | 5.050347e-03 | -0.101248589 | significant |
| D0201 | 0.092234219 | 0.260028653 | 8.340902e-04 | 2.407488e-03 | -0.167794434 | significant |
| D0202 | 0.160795013 | 0.371123533 | 5.618966e-05 | 3.161839e-04 | -0.210328521 | significant |
| D0203 | 0.342605111 | 0.471551663 | 3.432236e-05 | 2.564082e-04 | -0.128946551 | significant |
| D0204 | 0.250243216 | 0.395633777 | 2.306458e-03 | 5.050347e-03 | -0.145390561 | significant |
| D0205 | 0.063752861 | 0.169920437 | 7.121052e-05 | 3.617495e-04 | -0.106167576 | significant |
| D0206 | 0.147551315 | 0.443090128 | 5.618966e-05 | 3.161839e-04 | -0.295538813 | significant |
| D0207 | 0.412156668 | 0.558207530 | 2.090231e-02 | 3.447523e-02 | -0.146050862 | significant |
| D0208 | 0.155823369 | 0.301738922 | 5.618966e-05 | 3.161839e-04 | -0.145915553 | significant |
| D0209 | 0.131997770 | 0.352678185 | 6.549873e-06 | 9.242598e-05 | -0.220680415 | significant |
| D0210 | 0.133702102 | 0.284613983 | 1.177172e-05 | 1.359099e-04 | -0.150911881 | significant |
| D0212 | 0.133552981 | 0.422562064 | 6.549873e-06 | 9.242598e-05 | -0.289009083 | significant |
| D0213 | 0.126218478 | 0.306630447 | 8.340902e-04 | 2.407488e-03 | -0.180411970 | significant |
| D0305 | 0.366492686 | 0.423996527 | 4.939623e-03 | 9.802064e-03 | -0.057503841 | significant |
| D0306 | 0.146105878 | 0.434641186 | 6.549873e-06 | 9.242598e-05 | -0.288535308 | significant |
| D0501 | 0.790847790 | 0.872992541 | 1.805380e-02 | 3.016885e-02 | -0.082144750 | significant |
| D0502 | 0.480358478 | 0.285918054 | 4.781407e-04 | 1.557022e-03 | 0.194440424 | significant |
| D0503 | 0.125879327 | 0.000000000 | 6.866156e-07 | 4.360009e-05 | 0.125879327 | significant |
| D0505 | 0.286597240 | 0.350858031 | 8.641809e-03 | 1.567871e-02 | -0.064260791 | significant |
| D0506 | 0.211360464 | 0.391670686 | 6.549873e-06 | 9.242598e-05 | -0.180310222 | significant |
| D0507 | 0.110052668 | 0.210004157 | 1.125340e-04 | 4.610265e-04 | -0.099951489 | significant |
| D0509 | 0.440041988 | 0.526487614 | 1.125601e-02 | 1.931774e-02 | -0.086445625 | significant |
| D0510 | 0.000000000 | 0.013573683 | 2.308808e-04 | 7.924829e-04 | -0.013573683 | significant |
| D0511 | 0.611751724 | 0.767405683 | 1.665215e-03 | 3.916339e-03 | -0.155653959 | significant |
| D0513 | 0.224858211 | 0.438902945 | 3.155375e-03 | 6.678878e-03 | -0.214044734 | significant |
| D0601 | 0.034174614 | 0.141369358 | 2.997491e-02 | 4.758517e-02 | -0.107194744 | significant |
| D0602 | 0.000000000 | 0.030499587 | 2.308808e-04 | 7.924829e-04 | -0.030499587 | significant |
| D0606 | 0.003034342 | 0.043637689 | 5.152105e-05 | 3.161839e-04 | -0.040603346 | significant |
| D0607 | 0.008552574 | 0.041697052 | 2.096373e-03 | 4.840715e-03 | -0.033144478 | significant |
| D0608 | 0.000000000 | 0.002444638 | 3.625355e-03 | 7.547870e-03 | -0.002444638 | significant |
| D0609 | 0.158687978 | 0.084565489 | 1.403581e-04 | 5.401660e-04 | 0.074122489 | significant |
| D0610 | 0.000000000 | 0.007160308 | 1.522953e-03 | 3.916339e-03 | -0.007160308 | significant |
| D0702 | 0.455688142 | 0.326464654 | 2.635404e-02 | 4.236663e-02 | 0.129223488 | significant |
| D0705 | 0.323241782 | 0.258159545 | 2.306458e-03 | 5.050347e-03 | 0.065082237 | significant |
| D0706 | 0.059976159 | 0.148351231 | 1.665215e-03 | 3.916339e-03 | -0.088375073 | significant |
| D0807 | 0.015074471 | 0.041747020 | 8.978999e-05 | 4.072617e-04 | -0.026672549 | significant |
| D0816 | 0.043641253 | 0.091390659 | 8.340902e-04 | 2.407488e-03 | -0.047749406 | significant |
| D0817 | 0.005827776 | 0.019925548 | 1.445050e-03 | 3.823361e-03 | -0.014097772 | significant |
| D0907 | 0.162914556 | 0.328681837 | 9.967024e-04 | 2.751765e-03 | -0.165767281 | significant |
| D0908 | 0.305403136 | 0.623522292 | 3.432236e-05 | 2.564082e-04 | -0.318119156 | significant |
| D0910 | 0.124407773 | 0.396891803 | 1.125340e-04 | 4.610265e-04 | -0.272484030 | significant |
| term | df | SumOfSqs | R2 | statistic | p.value |
|---|---|---|---|---|---|
| environment | 1 | 18.732917 | 0.27521376 | 11.099093 | 0.001 |
| river | 2 | 5.451379 | 0.08008868 | 1.614948 | 0.148 |
| Residual | 26 | 43.882492 | 0.64469756 | NA | NA |
| Total | 29 | 68.066788 | 1.00000000 | NA | NA |
12.3.3 Marginal
Wilcoxon rank sum exact test
data: mci by environment
W = 56, p-value = 0.03277
alternative hypothesis: true location shift is not equal to 0# A tibble: 33 × 5
gift high low p_value p_adjust
<chr> <dbl> <dbl> <dbl> <dbl>
1 B0221 0.177 0.527 0.00268 0.0297
2 B0605 0.0886 0.396 0.00663 0.0371
3 B0709 0 0.0329 0.000980 0.0196
4 B1028 0.00776 0.0891 0.00224 0.0297
5 D0101 0.00637 0.0634 0.00261 0.0297
6 D0103 0.0689 0.216 0.00839 0.0435
7 D0201 0.0589 0.252 0.00276 0.0297
8 D0202 0.110 0.323 0.00820 0.0435
9 D0203 0.214 0.424 0.00932 0.0450
10 D0204 0.225 0.483 0.00631 0.0368
# ℹ 23 more rows| gift | high | low | p_value | p_adjust | difference | significance |
|---|---|---|---|---|---|---|
| B0221 | 0.177144655 | 0.52701883 | 2.677235e-03 | 0.029723307 | -0.34987417 | significant |
| B0605 | 0.088604745 | 0.39623709 | 6.627165e-03 | 0.037112124 | -0.30763234 | significant |
| B0709 | 0.000000000 | 0.03290746 | 9.803796e-04 | 0.019607591 | -0.03290746 | significant |
| B1028 | 0.007758061 | 0.08906279 | 2.236734e-03 | 0.029723307 | -0.08130473 | significant |
| D0101 | 0.006371054 | 0.06336166 | 2.607633e-03 | 0.029723307 | -0.05699060 | significant |
| D0103 | 0.068861705 | 0.21552103 | 8.387951e-03 | 0.043493078 | -0.14665933 | significant |
| D0201 | 0.058876923 | 0.25212032 | 2.760021e-03 | 0.029723307 | -0.19324339 | significant |
| D0202 | 0.110126355 | 0.32295102 | 8.200669e-03 | 0.043493078 | -0.21282467 | significant |
| D0203 | 0.213841081 | 0.42380897 | 9.322462e-03 | 0.045004989 | -0.20996789 | significant |
| D0204 | 0.225490303 | 0.48319440 | 6.306083e-03 | 0.036785487 | -0.25770410 | significant |
| D0205 | 0.064765347 | 0.17098720 | 9.226787e-03 | 0.045004989 | -0.10622185 | significant |
| D0208 | 0.113400443 | 0.25966177 | 4.235560e-03 | 0.032943248 | -0.14626132 | significant |
| D0209 | 0.101669651 | 0.28432354 | 1.758623e-03 | 0.027356358 | -0.18265389 | significant |
| D0212 | 0.172471768 | 0.29920957 | 1.048346e-02 | 0.046042591 | -0.12673780 | significant |
| D0213 | 0.094273805 | 0.26659680 | 3.217419e-03 | 0.030029244 | -0.17232300 | significant |
| D0301 | 0.000000000 | 0.07340385 | 6.096424e-03 | 0.036785487 | -0.07340385 | significant |
| D0302 | 0.004398428 | 0.08700617 | 2.275440e-04 | 0.006371233 | -0.08260774 | significant |
| D0304 | 0.009925215 | 0.22320473 | 5.606955e-05 | 0.002616579 | -0.21327951 | significant |
| D0307 | 0.015936692 | 0.24428734 | 1.718478e-04 | 0.006014672 | -0.22835064 | significant |
| D0308 | 0.119232778 | 0.32375506 | 5.354418e-03 | 0.036785487 | -0.20452228 | significant |
| D0502 | 0.059489928 | 0.55204220 | 1.708261e-05 | 0.001195782 | -0.49255228 | significant |
| D0503 | 0.018551988 | 0.14195916 | 1.085290e-02 | 0.046042591 | -0.12340717 | significant |
| D0509 | 0.273367616 | 0.53084131 | 1.054085e-02 | 0.046042591 | -0.25747370 | significant |
| D0518 | 0.092542585 | 0.27773775 | 4.091025e-03 | 0.032943248 | -0.18519517 | significant |
| D0603 | 0.000000000 | 0.10245182 | 6.096424e-03 | 0.036785487 | -0.10245182 | significant |
| D0607 | 0.009275994 | 0.10179302 | 6.834773e-04 | 0.015947804 | -0.09251702 | significant |
| D0611 | 0.000000000 | 0.14970317 | 6.096424e-03 | 0.036785487 | -0.14970317 | significant |
| D0704 | 0.163489399 | 0.43901684 | 3.994756e-03 | 0.032943248 | -0.27552744 | significant |
| D0706 | 0.003315462 | 0.10115430 | 5.202430e-03 | 0.036785487 | -0.09783884 | significant |
| D0807 | 0.006303428 | 0.21451084 | 1.251696e-05 | 0.001195782 | -0.20820742 | significant |
| D0816 | 0.035535517 | 0.22732398 | 3.217419e-03 | 0.030029244 | -0.19178846 | significant |
| D0817 | 0.002166158 | 0.01700964 | 1.492190e-03 | 0.026113324 | -0.01484348 | significant |
| D0904 | 0.095233051 | 0.00000000 | 1.053795e-02 | 0.046042591 | 0.09523305 | significant |
| term | df | SumOfSqs | R2 | statistic | p.value |
|---|---|---|---|---|---|
| environment | 1 | 22.66237 | 0.11067970 | 3.415318 | 0.021 |
| river | 2 | 16.20626 | 0.07914899 | 1.221177 | 0.235 |
| Residual | 25 | 165.88774 | 0.81017131 | NA | NA |
| Total | 28 | 204.75637 | 1.00000000 | NA | NA |
